It is not uncommon to see the amount of data associated with a business venture grow at an exponential pace. Thus, a variety of techniques to compress large amounts of data have been developed in an attempt to conserve storage resources. While algorithmic data compression may operate to reduce database table storage space and input/output (I/O) access cycle time, these benefits may come at the cost of increased processing effort to decompress the compressed data when queries are made, or when the data values are updated.